《天然药物化学》课程参考文献（天然药物研究与开发）Advancing the Drug Discovery and Development Process

Angewangrtays Drug Development D01:10.1002/anie,201404761 Advancing the Drug Discovery and Development Process K.C.Nicolaou" Dedicated to professor madeleine foullie on the occasion of her 87th birthday The current state of affairs in the drug discovery and development process is briefly summarized and then ways to take advantage of the ever increasing fundamental knowledge and tech mous c es.diagnos nical knowhow in chemistry and biology and related disciplines are discussed.The primary cal industry still face motivation of this Essay is to celebrate the great achievements of chemistry,biology,and medi cine and to inform and inspire students and ha nanges and academics to enter the field of drug discovery and development while,at the same time. continue to advance the fundamentals of their disciplines. ake a major transd isciplinary approach inv oing clini an meant to encourage and aphers and other structural biologists chen ndustry mputational exp and I merge covery and d nent to and th ts of the uss also nowever.are high,as the causes of dn espec 1.Introduction The recent suce es of the pha maccutical enterpris the hu has to eutic index.This pre ss is often a n natter of life Indeed the cur are in th vith th anagem t.and cure of dis discoverers in e pharm tical and bic gy indus at the end of the nineteenth century marked by the hins mav provide a uniaue eplatform for advancing the art and cience of drug discovery and development 的Prof.K.C..Nic 9128 Wiley Online Library

Drug Development DOI: 10.1002/anie.201404761 Advancing the Drug Discovery and Development Process K. C. Nicolaou* Dedicated to Professor Madeleine Joulli on the occasion of her 87th birthday academic–industrial partnerships · biological assays · biological targets · drug design · organic synthesis 1. Introduction The recent successes of the pharmaceutical enterprise are undeniable and extraordinary. Admirable as it is, the drug discovery and development process is one of the most challenging and difficult human endeavors, for it has to balance efficacy in health benefits with safety at an appro￾priate therapeutic index. This process is often a matter of life and death for patients; their cures are in the hands of scientists and clinicians who discover, develop, and administer medications for prevention, management, and cure of disease, injuries, and other disorders. Emerging from organic synthesis at the end of the nineteenth century,[1] as marked by the introduction of Aspirin, modern medicine has changed the world[2] and, in many ways, how we live and die. Aided by discoveries in biology and chemistry, modern pharmaceutical industry has made enormous contributions to society by continuously providing new medicines, diagnostics, and dis￾ease-preventing agents. Despite these impressive advances, however, the pharmaceutical industry still faces enormous scientific and financial challenges, with some watchers of the industry believing it is encountering an unprecedented crisis. It is apparent that continuous changes and improvements are both inevitable and needed. But how to bring about these changes? From the scientific and technical points of view, and because of its magnitude and complexity, this project should be viewed as an ongoing “Grand Challenge.” Indeed, it will take a major transdisciplinary approach involving clinicians, biologists, medicinal and synthetic organic chemists, X-ray crystallographers and other structural biologists, chembioin￾formaticians, computational experts, and logicians, among others, working collaboratively and synergistically toward improved paradigms for drug discovery and development to bring about a substantial change. Strategic and resource aspects of the process also need to be continuously reeval￾uated by management, and modified accordingly for opti￾mized productivity and cost. The prospects for success, however, are high, as the causes of the failures in the drug discovery and development process are understood, for the most part, at least by those responsible for discovering and developing drug candidates. Indeed, and much to their credit, biomedical researchers appear to be cognizant not only of the problems associated with some of the current practices, but also of possible solutions and improvements of the drug discovery and development process. This Essay is meant to inspire and motivate, especially those in academia, to think about how to use their expertise to contribute to the drug discovery and development process. Indeed, the freedom and flexibility offered by academia are conducive to risky ideas that can be pursued in collaboration with the expert drug discoverers in the pharmaceutical and biotechnology indus￾tries for optimal success. Thus, academic–industrial partner￾ships may provide a unique platform for advancing the art and science of drug discovery and development. [*] Prof. K. C. Nicolaou Department of Chemistry, Rice University 6100 Main Street, Houston, TX 77005 (USA) E-mail: kcn@rice.edu The current state of affairs in the drug discovery and development process is briefly summarized and then ways to take advantage of the ever￾increasing fundamental knowledge and tech￾nical knowhow in chemistry and biology and related disciplines are discussed. The primary motivation of this Essay is to celebrate the great achievements of chemistry, biology, and medi￾cine and to inform and inspire students and academics to enter the field of drug discovery and development while, at the same time, continue to advance the fundamentals of their disciplines. It is also meant to encourage and catalyze multidisciplinary partnerships between academia and industry as scientists attempt to merge their often complementary interests and expertise to achieve new improvements and breakthroughs in their respective fields, and the common goal of applying them to the discovery and invention of new and better medicines, especially in areas of unmet needs. Angewandte . Essays 9128 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Angew. Chem. Int. Ed. 2014, 53, 9128 – 9140

behin the particularl nd the high attrition of drug candidates had the ext ed impact on drue dis ustry wh aders are umbe Rece some stunning,i disturbing er develo ely 18 billion Us dollars (exeludin iden ening of rando co a range of the total expendi the advent of rand ures du. preceding era and ed by pe of drus ering the d that"the of 93%and pat y r that disprop g.litigation).as ed to to reach.The of fa inical develo f ided fact ed and nd in the medicinal che n the olecule likely to displa Figure 1.Nu design programs in wh w) are fror the tare The imization from trial and ed 200 and od ab in tion c compound.the s alled Lipinski rule eight less than 500 Dalton (MW<500):calculated partition Angrw.Chem.int.Ed 2014.52 9128- andte.org 9129

2. Current State of Affairs in the Drug Discovery and Development Process Pressures from the sales of generic drugs and the high attrition of drug candidates are currently plaguing the pharmaceutical industry while its leaders are scrambling for new models and paradigms to improve the situation.[3–24] Recent analyses[11] reveal some stunning, if not disturbing statistics. The cost of developing a drug as of 2010 stood at approximately 1.8 billion US dollars (excluding target iden￾tification and validation and overhead costs; perhaps a range between 1–2 billion US dollars may be more descriptive) and rising. Clinical trials accounted for 63% of the total expendi￾tures, while the cost of preclinical drug discovery and development was estimated to be only 32% of the total cost. The duration of the process from target validation to approval was on average 13.5 years. Success rates (probability of the success of drug candidates entering the clinical pipeline/ Phase I) were estimated at 7% for small molecules and 11% for biologics (attrition rates of 93% and 89%, respective￾ly).[11] It is clear that disproportionate resources are expended on late-stage development (i.e., clinical trials) and post￾approval activities (e.g., marketing, litigation), as opposed to early-stage discovery and preclinical development. The post-penicillin period was a golden era for the pharmaceutical industry with many drugs being approved steadily and at increasing rates until the recent notable sluggish achievement of drug approvals. Indeed, the global number of drugs approved annually during the period 1981– 2013 did not increase significantly as expected (see Figure 1). Surprisingly to some, this phenomenon occurred despite the impressive strides made recently in chemistry and biology, the two major disciplines behind the process. It is particularly disappointing that the human genome project has not as yet had the expected impact on drug discovery, as measured by the number of drug approvals (see Figure 1), although there is no denying its beneficial impact on science and its future potential. Disappointingly, other developments that started in the 1990s, such as the combinatorial chemistry and high￾throughput screening of random compound libraries, also failed to impact dramatically the drug discovery and develop￾ment process despite their early promises. It is interesting to note that the advent of random combinatorial chemistry in the late 1980s coincided with the downsizing of natural products chemistry that had proved so productive in the preceding era and had been sparked by penicillins success. To the causes of the recent slowdown in drug approvals must also be added the fact that “the low-hanging fruits” (e.g., diseases associated with known pathogenesis, druggable biological targets, predictive in vitro and in vivo assays, and reliable clinical endpoints) have already been picked, and the realization that those remaining are becoming increasingly more challenging to reach. The blame of failure to deliver better drug candidates, however, cannot entirely be placed on these developments. Rather, it appears that the actual design of the synthesized molecules during the lead discovery and optimization phase of the process in past eras was sometimes misguided, a fact recognized and pointed out by medicinal chemists and other biomedical researchers. Indeed, a series of recent reviews and commentaries convincingly argue the case for improvements and new directions in the practices of drug design of the last few decades.[3–24] Currently, medicinal chemists have at their disposal, in addition to their experience and intuition, a number of guidelines and principles that have been developed over recent years to assist them in their endeavors as they proceed to design and optimize lead compounds to drug candidates. In most pharmaceutical companies, drug designers are also using computational models to select the best molecules for syn￾thesis. Such computational models help them understand whether the molecules are likely to display the desired ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. In addition, they employ several structure-based drug design programs in which X-ray crystal structures help them identify the optimum small molecules to fit the targeted receptors. The optimization process involves reiterative molecular design (computer-aided or not), syn￾thesis of the designed molecules, and biological evaluation of the synthesized compounds. Indeed, most structure–activity relationships (SARs) and other structure–property relation￾ships are presently derived from trial and error based experimentation rather than computational chemistry or other reliable predictive methods. The first systematic guide￾lines to be introduced in medicinal chemistry were those delineated by Lipinski and his collaborators in their landmark papers in 2001[4] and 2004.[5] For good absorption or perme￾ability of a compound, the so-called Lipinski rule of five (RO5) stipulates limits for certain parameters [i.e., molecular weight less than 500 Dalton (MW< 500); calculated partition Figure 1. Number of all new approved drugs during the 1981–2013 time period (globally, modified from Ref. [49]). *Data for 2011, 2012, and 2013 are from the FDA[71] (global data not availiable as of this writing). K. C. Nicolaou, born in Cyprus and edu￾cated in the UK and USA, holds the Harry C. and Olga K. Wiess Chair in Chemistry at Rice University. The impact of his work in chemistry, biology, and medicine flows from his contributions to chemical synthesis as described in over 750 publications. His commtiment to chemical education is re￾flected in his book series Classics in Total Synthesis and monograph Molecules That Changed the World, and his training of hundreds of graduate students and postdoc￾toral fellows. Angewandte Chemie Angew. Chem. Int. Ed. 2014, 53, 9128 – 9140 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim www.angewandte.org 9129

Angewandte ent les general are rs(HB 10- ate hdc r potency but red by th (p) ma bons within a mo ecific lipophilic fact alone were exp ially h d.rir s of orption.solubility.cell pe eability and brain elipophilicity.and thus po d with fo and off-targe m number toler candidat ther with e ADMET cha behavior need to be optimally and appr count the entire molecular ass of th andida ave ser chemis mproving the properti of a npound as a drug can dat important ha and metrics aiming to quantitatively vide ): K=d nce for drug design are no n-pop [LLE in the drug-l able ned the S-til (QED).this tuit te ithm fref d to idat molecules anothe re )wh s the log D val lue at C is the unbound in ning the oretical and experimen al tud stability Thes and other mcdicinal cher d rule pro warrant tiny and most tructural motifs that make up thei for further me the of pi c b ular stru Matching molecular pair (MMP)analyses are large exogenous,i optimization as can point to elps sci tists to unde and and deconvolute the mecha property adj structure (e.g. alogen vs H,ester vs.OH, embark on drug discove and later durin relat hins could lead to a pow rful toolbox providin ogical targ ets and their bindin n vitr ADMET dy exist.and ent reports dem onstrate the u this ap s).the Center fo r Biologics Evalu successes Among the Protein Data Bank (PDB)and Mendeia 9130 ngewandte.org

coefficient less than five (clogP < 5); less than five hydrogen bond donors (HBDs < 5); and less than ten hydrogen bond acceptors(HBAs <10=2 5)]. To these parameters were later added the number of rotatable bonds (NRot, averaging around six in recent years); topological polar surface area (TPSA > 75, “3–75 rule”); and flatness as measured by the fraction of sp3 carbons (Fsp3 , ratio of sp3 carbons to the total number of carbons within a molecule) (Fsp3 < 0.47).[13] These parameter limits were expected to impart on the compound favorable properties such as suitable lipophilicity for desired levels of absorption, solubility, cell permeability, and brain barrier penetration. These properties are important to and are usually correlated with formulation, delivery, and off-target selectivities linked to toxicity. Together with metabolism (e.g., CYP oxidation), the ADMET characteristics of a drug or its pharmacokinetic behavior need to be optimally and appro￾priately balanced in order for a compound to become a viable drug candidate for clinical development. For the most part, these “rules” have served medicinal chemists well in the past few years, although notable exceptions are evident. Most importantly, medicinal chemists have introduced further refinements for their drug design efforts such as “ligand efficiency” [defined as LE = 1.4 logKi /number of heavy atoms (atoms other than H);[25] where Ki = dissociation constant; relates binding energy per heavy atom to in vitro potency], “ligand-lipophilicity efficiency” [LLE,[26, 27] also known as “lipophilic efficiency” (LipE),[28] defined as LLE = LipE = log10 (Ki or IC50)log D; relates lipophilicity to in vitro potency], “ligand-efficiency-dependent lipophilic￾ity” (defined as LELP = logP/LE),[29] the “central nervous system multiparameter optimization” algorithm [referred to as CNS MPO],[30] and “lipophilic metabolism efficiency” [defined as LipMetE = logD7.4log10 (CLint,u), where log D7.4 is the log D value at pH 7.4 and CLint,u is the unbound intrinsic clearance in human liver microsomes; relates lipophilicity to metabolic stability].[31] These and other medicinal chemistry design parameters promise to provide additional tools for rational drug design as more data sets emerge and are exploited appropriately. The properties of small organic molecules are, for the most part, translations of their molecular structures, the assemblies of the various structural motifs that make up their architectures. It is, therefore, not surprising that correlations of properties with certain structural motifs have been made by analysis of available data of known drugs, compounds that failed clinical trials, preclinical drug candidates, and other ligands. Matching molecular pair (MMP) analyses are be￾coming increasingly powerful tools for lead identification and optimization purposes as they can point to significant property adjustments by small structural changes.[32–36] MMP refers to compounds differing only in relatively small features in molecular structure (e.g., halogen vs. H, ester vs. OH, Me vs. iPr). The systematic build-up of such structure–activity relationships could lead to a powerful toolbox providing correlations of structural motifs with estimates of in vitro potencies and other properties, including ADMET. Several recent reports[33–36] demonstrate the usefulness of this ap￾proach in drug discovery programs while its adoption is spreading as a consequence of its early successes. Among the most valuable general conclusions are those pertaining to lipophilicity, potency, promiscuity, and solubility. Higher lipophilicity usually leads to higher potency but also results in higher aqueous insolubility and promiscuity, both of which are liabilities for the compound. It is important to note here that lipophilic efficiency (LLE and LipE) considerations may help to understand whether potency increases are due to nonspecific lipophilic factors alone or whether specific interactions are involved. Higher numbers of aromatic, especially benzenoid, rings within the structure of a molecule increase lipophilicity, and thus potency, while at the same time lower solubility. Three aromatic rings have been suggested as the maximum number tolerable for a drug candidate, although notable exceptions exist. A better measure for this structural requirement is perhaps the Fsp3 parameter, which takes into account the entire molecular assembly of the structure. Replacement of aromatic rings with sp3 structural motifs is currently considered as a favorable feature for improving the properties of a compound as a drug candidate. Increasing numbers of chiral centers has also been recognized as a desirable feature within the structures of potential drug candidates. The rules and metrics aiming to quantitatively provide guidance for drug design are not without issues, as evidenced by recent reports questioning their absolute predictivity and validity. For example, a new measure for the “drug-likeliness” of molecules has been proposed based on desirability (desirable properties). Called the quantitative estimate of “drug-likeliness” (QED), this intuitive metric reflects the distribution of molecular properties and can be used to rank candidate molecules.[37] In another more recent report, further doubts are cast on the validity of several of the so￾called efficiency indices and metric rules for drug design.[38] Combining theoretical and experimental data, this study provides convincing analysis of a number of examples and concludes that, at the least, the majority of the proposed rules and metrics have to be viewed with skepticism, leaving LipE and the originally proposed Lipinski rules as the only guidelines warranting further scrutiny and use. The recent proliferation of such criteria and rules are indeed in want of critical evaluation and ranking themselves, pointing to the need for further improvement of the drug discovery and development process with regards to predictivity of proper￾ties based on molecular structure. Intelligence gathering on known and emerging biological targets and their ligands, whether known drugs or otherwise, small or large molecules, endogenous or exogenous, is extremely important for drug discovery. Such knowledge helps scientists to understand and deconvolute the mecha￾nism of action of both the biological targets and their ligands and provides essential information to chemists and biologists as they embark on drug discovery programs, and later during the optimization phase. A number of databases containing useful informatics on biological targets and their binding ligands already exist, and include the DrugBank database, the Therapeutic Targets Database, the U.S. FDA Orange Book (for small-molecule drugs), the Center for Biologics Evalua￾tion and Research (CBER) website (for biological drugs), the Protein Data Bank (PDB), and the Online Mendelian Angewandte . Essays 9130 www.angewandte.org 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Angew. Chem. Int. Ed. 2014, 53, 9128 – 9140

Inhe MIM)(for genen es).Analyse arthritis,mul e scler Abh and oth d to the ar the findings that only a fev he othe au mains d thera eutic d s b)th antil the drug polyp eains it is int to note that curr HER Th emis to design and ica's Bio harmac that it ha othe ers)in ent (Pha sI-I an app appro its p of drug Serg 12010 Cla fied in se ets d ing (GPCRs T egor xidoreduc (1).and other groups (2).Within the trar oltage-gal 00 channels(29).oth cs(total90 in clin cal de (1 porters (3). and auxiliar tra nerica's Bic 2 d by the FDAli D that e than 100 diseases (cance r.38;infectious disea rate of s n of targets over th thers in ng diabe and digestive.genetic. s to pus e"hi is i dramatic incr thcare to new he ghts Identifyi which t of the rug d nd hat aturel d tempt s for temoe are currently being hotly p Most of the drue d ne19s22010e ng th and inclu argeting r sand na n the mea h ver.the numbers of biologic drugs ength.for each approach has its own I an ncrea in the las对 and enym g a mor than f le trend has emerged last few years a d by the CD20 B-h mphocyte antigen.used to treat rheumatoid ed against the mutant BRC-ABL kinase and used for the Chem.mtEd2014..9128-914 ndte org 93

Inheritance of Man (OMIM) (for genetic diseases). Analyses of data from these databanks reveal interesting facts and trends. Among them are a) the findings that only a few hundred targets, and even fewer privileged druggable do￾mains, account for all the approved therapeutic drugs, b) the emergence of target families [gene families, e.g., protein kinases, G protein coupled receptors (GPCRs)], and c) the recognition of the importance of drug polypharmacology (binding to and modulation of several targets).[6] In this respect, it is interesting to note that current knowledge places the number of human genes to 25 000, human proteins to 200 000, and human cells to 12 trillion.[39] The task of the medicinal chemist to design and synthesize a molecule that would navigate selectively to its target is enormous. The fact that it has been done so many times is a tribute to medicinal chemists and those other scientists that contributed so brilliantly to bring the state of affairs in drug discovery to its present admirable condition. Recent analyses of drug targets and their ligands revealed further useful intelligence and insights.[16] Thus, up to 2010, 435 effect-mediating biological targets in the human genome were modulated by 989 drugs through 2242 binding inter￾actions.[16] Classified in several groups, these targets include the families of receptors (193), enzymes (97), transporter proteins (67), and others (51). Among the latter group are enzyme-interacting proteins, structural and adhesion proteins, and ligands. The receptor group includes G protein coupled receptors (GPCRs, 82), ligand-gated ion channels (39), tyrosine kinases (22), immunoglobulin-like receptors (21), nuclear receptors (17), and other receptors (12). The enzyme category includes the families of oxidoreductases (22), trans￾ferases (21), hydrolases (43), lyases (3), isomerases (5), ligases (1), and other groups (2). Within the transporter protein class are the voltage-gated ion channels (29), other ion channels (6), solute carriers (12), active transporters (7), other trans￾porters (3), and auxiliary transport units (10). Database analyses also revealed that from 1982 to 2010, a total of 520 drugs were approved by the FDA.[16] Derived from these studies were also the conclusions that most of these drugs operate on previously targeted human proteins, and that the rate of successful modulation of targets over the last 30 years has been stable. In the last few decades only a few new “druggable” biological targets have emerged each year. This is in contrast to the rather dramatic increase in investment and despite the impressive advances made in biology and chemistry over this period. This dissymmetry may be traced to a number of reasons, including the aforementioned “low￾hanging fruits” explanation, pressures to deliver drug candi￾dates prematurely, and temptations for temporary gains at the drug candidate optimization phase vs. long-term benefits. Most of the drugs discovered in the 1982–2010 period were small molecules and include those targeting novel biological targets. In the meantime, however, the numbers of biologic drugs such as monoclonal antibodies, fusion proteins, and enzymes have been steadily increasing in the last two decades, demonstrating a more than fashionable trend. These include antibodies [for example, rituximab (Rituxan, Roche; binds to CD20 B-lymphocyte antigen, used to treat rheumatoid arthritis, multiple sclerosis, and other autoimmune diseases), adalimumab (Humira, Abbott; binds to TNFa, used to treat rheumatoid arthritis and other autoimmune diseases) and trastuzumab (Herceptin, Genentech; used against HER2 positive breast cancer)] and antibody drug conjugates (ADCs) with cytotoxic drugs as payloads for targeted cancer chemotherapy [e.g., brentuximab vedotin (Adcetris, Seattle Genetics and Millenium/Takeda; used against advanced Hodgkins lymphoma) and trastuzumab emtansine (Kadcyla, Genentech/Roche; used against late-stage HER2 positive breast cancer)]. Biologics will continue to be on the rise as drugs and drug candidates. Indeed, a recent report from Americas Biopharmaceutical Research Companies[39] lists 907 biologic drug candidates (antisense, cell therapy, gene therapy, monoclonal antibodies, recombinant proteins, vac￾cines and others) in clinical development (Phases I–III and pending application for approval, see Figure 2). Targeting more than 100 diseases (cancer, 38; infectious diseases, 176; autoimmune diseases, 71; cardiovascular diseases, 58; and others, including diabetes and digestive, genetic, neurologic, and respiratory disorders), these drugs promise to push the frontiers of science and medicine to new domains and advance healthcare to new heights. Identifying which drugs will help which patients and following up with personalized medicines is clearly the new paradigm in medicine and will certainly contribute to the improvement of the drug discovery and development process and better healthcare for the patients. While biologics are currently being hotly pursued, we should not allow the success of any given modality to swing the pendulum too far in one direction and certainly not away from small molecules and natural products. Indeed the complementarity of each approach should be exploited and viewed as a strength, for each approach has its own advantages and disadvantages. Another powerful trend, that of multitargeting drugs,[40, 41] has emerged over the last few years as marked by the introduction of imatinib (Gleevec, Novartis). Initially target￾ed against the mutant BRC-ABL kinase and used for the Figure 2. Number of biologics (total 907) in clinical development (phases I–III and approval process) by product category (2013 report from America’s Biopharmaceutical Research Companies).[39] Angewandte Chemie Angew. Chem. Int. Ed. 2014, 53, 9128 – 9140 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim www.angewandte.org 9131

Angewandte rcatnmcniofct cukemia(CML).imatinib Advancing the Drug Design and Development drug is eof the d er typ ery and opmer ery.Ne ork phar and .the o this argeting for of disea hat paradoxical affai and bi ld be de all of th inform on st organic synt enot an the p plan s for al.To h nt n ures t dru ich n ng or ted hat try molecule (no mpr nts in al dru 550. logP be een 3. 5.5.and TPSA of 60-90A ent and in the ral op use ron atic system ring (with Thus ngther in lubilizins uch as m .computat hrough in le would ha nost likel aio ction step st d The latter a c nding nd valid It is impr nd ph mnd and more predictiv to their dr covery effor s.matchi acilitated by the ever- creasing power of computer And y for m eimer's and types of cancer re (Le 00g speed)shoul un dertake the challenge of improving even further the drug like as they attemnt to carrv their respective task d ery and d nd bi logica targe 山gan strategic initiatives that could bring within reach cures for MMPs) bionmkenahdbioiogeaiasayseoudpg 9132 www.angewandte.org 914

treatment of chronic myelogenous leukemia (CML), imatinib was later found to bind to several kinases. Another impressive example of a multikinase inhibitor drug is sorafenib (Nexavar, Bayer). Approved by the FDA in 2005 for the treatment of advanced renal cell carcinoma, this drug is now employed for a number of other cancer types. This approach of multitarget drug mechanism of action is becoming a new paradigm in drug discovery. Network pharmacology and polypharmacol￾ogy,[40, 41] two relatively new directions in biomedical research, aim at understanding and exploiting this new strategy of molecular targeting for the treatment of disease.[6] The overarching new paradigm of both small-molecule drugs and biologics aims at more targeted strategies to cure disease without collateral damage that often leads to undesired side effects due to off-target promiscuity. Despite all of the new information on structural motifs and the properties they impart, and technological advantages in organic synthesis, the drug discovery and development process still fails to realize gains in the number of drug candidates successfully crossing the finish line of clinical trials and approval. To be fair to the medicinal chemists, we should note that drug candidates fail not only due to deficiencies in their molecular structures but also, and most importantly, because of lack of full understanding of the pathogenesis and biology of the disease. It has been estimated that, on average, 10 000 compounds are synthesized and tested before one of them makes it to the clinic as an approved drug. It is also interesting to note that analyses of several databases suggest that a “typical” medicinal chemistry molecule (not necessarily an actual molecule)[13] has a molecular weight in the range of 350–550, log P between 3.5–5.5, and TPSA of 60–90 2 ; it possesses 0–2 chiral centers, 30–50% of its carbon atoms are in the sp3 configuration, and it contains a biaryl bond linking a fused aromatic system and another ring (with one of the rings being a benzenoid). The typical molecule is also likely to contain a “solubilizing” group such as morpholine or piper￾azine bridged through a linker to an aryl ring, an amide, and an aromatic ring carrying a fluoride or chloride residue. This “typical” molecule would have most likely been synthesized in four to six steps that included an amide bond formation, a deprotection step (most probably a Boc removal from a structural motif introduced from a commercially available building block), and a palladium-catalyzed cross-coupling reaction (most likely a Suzuki reaction).[13] It is also of interest that the average potency of approved drugs is around 20 nm. Synthetic organic chemists have made impressive strides in their science and medicinal chemists have performed admirably in applying some of the emerging technologies in organic synthesis to their drug discovery efforts, matching the enormous advances made by biologists and clinicians in their domains. And yet a number of menacing diseases such as Alzheimers and certain types of cancer remain untreatable. To be sure, scientists and clinicians are capable and poised to undertake the challenge of improving even further the drug discovery and development process by systematic diagnostic and corrective actions through collaborative efforts and new strategic initiatives that could bring within reach cures for some of the remaining intransigent diseases. 3. Advancing the Drug Design and Development Process As convincingly argued by medicinal chemists and other pharmaceutical experts, the art and science of the drug discovery and development process needs changes and new paradigms.[4–24] However, due to the immense complexity of the drug discovery process, the response to this challenge can only be slow, under current conditions, despite the issues and uncertainties associated with the pharmaceutical industry. This somewhat paradoxical state of affairs becomes even more puzzling if we consider the modern instrumentation and technologies that could be deployed to address the remaining challenges. These sharp tools and powerful technologies include computer power and computational methods, chem￾bioinformatics, organic synthesis, genomics, biological assays, animal models (when appropriately predictive), and cognitive science. Among the possible explanations for this slow, rather than decisive move toward new paradigms of drug discovery and development, the more likely reasons are perhaps the current pressures to deliver drug candidates in shorter and shorter times, considerations of cost in manufacturing the drug if approved (which provides resistance to employ costly materials and modern synthetic technologies), and lack of appreciation of the enormous long-term medical and eco￾nomic benefits to be derived from such improvements (a phenomenon that leads, in turn, to favoring instead short￾term and temporary gains). Improvements in the classical drug discovery and devel￾opment process (see Figure 3, center; main pipeline indicated by red arrow) may come from recent and pending advances in chembioinformatics, computational methods and computer modeling (Figure 3, top), and chemistry and biology (Fig￾ure 3, bottom). Thus, strengthening and encouraging integra￾tion of intelligence gathering and processing using modern computer power, computational methods, cognitive science, and continuously updated databanks could provide a major boost to the theoretical and chembioinformatics components of the drug discovery and development process, while major innovations may be derived from modern chemical, biolog￾ical, and pharmacological developments. The latter should include a better understanding and validation of biological targets,[42] epigenetics,[43] diagnostic biomarkers, and clinical endpoints, new and improved biological and pharmacological in vitro and in vivo assays, wider applications of modern organic synthesis strategies and methods, novel structural motifs[44–46] and compound libraries, and more predictive early-phase clinical trials. Facilitated by the ever-increasing power of computers, computational methods and cognitive science, continuously updated databanks, and useful programs for mining them rapidly (i.e., “google-like” efficiency and speed) should become routine and accessible to biologists and chemists alike as they attempt to carry out their respective tasks. Databanks of biological targets and biological target–ligand matched pairs (TLMPs), matching molecular pairs (MMPs),[32–36] biomarkers, and biological assays could provide crucial intelligence and assistance for the target identification and validation and lead identification and optimization Angewandte . Essays 9132 www.angewandte.org 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Angew. Chem. Int. Ed. 2014, 53, 9128 – 9140